WE1.M1.5

Toward data quality evaluation in pre-train dataset for remote sensing foundation model

Rui Liu, Hongsheng Zhang, The University of Hong Kong, China; Jing Ling, Guangdong University of Technology, China
Session:
WE1.M1: The Prospect of Remote Sensing Foundation Models: From Generation to Application Oral
Track:
Community-Contributed Sessions
Location:
Mezzanine: Room M1
Presentation Time:
Wednesday, 6 August, 09:00 - 09:15
Session Co-Chairs:
Rui Liu, The University of Hong Kong and Hongsheng Zhang, The University of Hong Kong
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Session WE1.M1
WE1.M1.1: SELF-SUPERVISED PRE-TRAINING FOR MULTI-TEMPORAL REMOTE SENSING IMAGERY BY JOINT EMBEDDING LEARNING
Qi Guo, Wuhan University, China; Jue Wang, Beijing Institute of Technology, China; Yinhe Liu, Yanfei Zhong, Wuhan University, China
WE1.M1.2: SSL-LIP: A two-stage Pre-training foundation model for SAR images
Yi Yang, Qingchen Fang, Xiaokun Zhang, Haipeng Wang, Fudan University, China
WE1.M1.3: MULTISPECTRAL TO HYPERSPECTRAL USING PRE-TRAINED FOUNDATIONAL MODEL
Ruben Gonzalez, Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany, Germany; Devyani Lambhate, Joao Lucas de Sousa Almeida, Paolo Fraccaro, Benedikt Blumenstiel, IBM Research, India; Conrad Albrecht, Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany, Germany; Thomas Brunschwiler, IBM Research, Germany; Nassim Ait Ali Braham, Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany, Germany; Ranjini Bangalore, IBM Research, India
WE1.M1.4: A GENERALIZED DEEP LEARNING METHOD FOR ROOFTOP CONDITION ASSESSMENT VIA MONOCULAR IMAGERY
Xinyu Li, The University of Tokyo, Japan; Zhiling Guo, Jian Xu, The Hong Kong Polytechnic University, China; Wei Yuan, Tohoku University, Japan; Xiaoya Song, Haoran Zhang, Peking University, China; Jinyue Yan, The Hong Kong Polytechnic University, China
WE1.M1.5: Toward data quality evaluation in pre-train dataset for remote sensing foundation model
Rui Liu, Hongsheng Zhang, The University of Hong Kong, China; Jing Ling, Guangdong University of Technology, China
Resources
No resources available.